Pawel Pawlewski

Cooperative Purchasing of Logistics Services among Manufacturing Companies Based on Semantic Web and Multi-agent System

The common access to the broadband Internet allows small and medium enterprises (SME) simpler participation in various supply chains [3]. However the main problem still is lack of consistency between processes which are undertaken by various supply chain participants. The aim of this paper is to propose the concept of broader cooperation between manufacturing companies based on semantic web and multi-agent system. The background of this paper refers to previous experiences of the authors by implementation of the CORELOG project. It promotes cooperation in logistics services among manufacturing companies located in the Bologna metropolitan area in order to increase companies’ competitiveness as well as environmental sustainability through the rationalization of the logistics processes. The application of semantic web and multi-agent system in the above mentioned project allows the efficient automatic data collection about logistics services providers and their resources, as presented in the Internet.

DES/ABS Approach to Simulate Warehouse Operations

The paper presents the results of research performed in the area of modeling and simulation of warehouse operations in a supply chain. Author defines in details main problems concerning warehousing. “Old” and “new” approaches to modeling and simulating are compared based on available simulation programs on the market. Main goal of the paper is to answer the question how to prepare in a very short time the motion of forklifts in a defined simulation model based on picking lists. Author proposes a method based on mixing DES (Discrete Event) and ABS (Agent Based Simulation). As result the library of agents objects (LogABS) is described and explained.

Scheduling of Mobile Robots with Preemptive Tasks

This paper deals with the problem of scheduling of mobile robots taking into account preemption cases in a flexible manufacturing system (FMS). In addition to capability of transporting materials between some machines, mobile robots are able to perform manufacturing tasks at other machines by using their manipulation arms. These manufacturing tasks can be preempted to allow mobile robots to transport materials when needed. The performance criterion is to minimize time required to complete all tasks, i.e. makespan. A mixed-integer programming (MIP) model is formulated to find the optimal solutions for the problem. Numerical experiments are investigated to demonstrate results of the proposed approach.

Multimodal Processes Rescheduling: Cyclic Steady States Space Approach

The paper concerns cyclic scheduling problems arising in a Multimodal Transportation Network (MTN) in which several unimodal networks (AGVs, hoists, lifts, etc.) interact with each other via common shared workstations as to provide a variety of demand-responsive material handling operations. The material handling transport modes provide movement of work-pieces between workstations along their manufacturing routes in the MTN. The goal is to provide a declarative framework enabling to state a constraint satisfaction problem aimed at AGVs fleet match-up scheduling taking into consideration assumed itineraries of concurrently manufactured product types. In that context, treating the different product types as a set of cyclic multimodal processes is the main objective to discuss the conditions sufficient for FMS rescheduling imposed by production orders changes. To conclude, the conditions sufficient for an FMS rescheduling imposed by changes of production orders treated as cyclic multimodal processes are stated as the paper’s main contribution.

Multiagent Approach for Supply Chain Integration by Distributed Production Planning, Scheduling and Control System

The changing business environment in which manufacturers are acting creates the need for more effective production processes planning, scheduling and control methods that are able to deal with uncertainties inherent in internal processes and external deliveries. The aim of the paper is to introduce the multiagent approach method for production planning, scheduling and control applicable in conditions of supply chain (SC) able to overcome the limitation of standard MRP/ERP systems in changing environment. Traditional approaches very often do not consider the influence of uncertainty inherent in production processes and supplies. Therefore, there is a need for the integration of manufacturing process planning, scheduling and control systems for generating more realistic and effective plans. Conceptual framework for the multiagent approach method involves the hybrid solutions combining the advantages of MRP simple logic and theory of constrains (TOC) ability to synchronize all production and material flow in supply chain. Authors discuss how application of TOC buffers monitoring procedures can help to improve the control of synchronized production and material flow in supply chain.

A fuzzy weighted average approach for selecting portfolio of new product development projects

New product portfolio selection is a multi-criteria decision making problem including both qualitative and quantitative criteria. Determining the exact values for these criteria is often difficult or even impossible taking into account uncertainty and complexity associated with new product development projects. To assist managers in making portfolio selection decisions, this study proposes a new project portfolio selection model that uses a fuzzy weighted average approach for ranking new product projects and artificial neural networks for estimating project performance. New product development projects are evaluated according to criteria related to marketing, project team, project performance, risk, and strategy. The use of neural networks enables more precise evaluation of project performance criteria and provides additional information in portfolio selection. A case study of the evaluation of new product projects illustrates the usefulness of the proposed approach.

Production flow control in the automotive industry – quick scan approach

The automotive industry is highly competitive. Manufacturers have to effectively control very complex production processes in order to fulfil customers’ orders for customised cars on time. The automobile assembly plants are highly stabilised production systems. However, uncertainty is still inherent in such systems. The aim of the paper is to propose a method that might be applied for a quick scan of the production flow in an assembly plant. The authors briefly present the theoretical background of the research and they discuss the main problems that have appeared by analyses of the uncertainty influence on the manufacturing operations performance. The classification of disturbance sources is provided as well as a detailed description of the case study and numerical example.

Using Multi-agent System for Improving and Implementing a New Enterprise Modeling Tool

GRAI Methodology is one of the three main methodologies for enterprise modeling (with PERA and CIMOSA). To support this methodology different tools are being developed. GRAIXPERT is a hybrid expert system for detecting inconsistencies in enterprises. GRAISUC is a module for choosing and implementing supply chain management tool in enterprises. GRAIQUAL is a module for improving quality system of enterprises. These modules are based on the use of different reasoning (Case-based reasoning (CBR), decomposition, transformation) but also on the enterprise knowledge management. The enterprise knowledge could be explicit or tacit. Each case of enterprise studied allows to improve the knowledge of the tool. Then, Multi-agent systems are used for acquiring this knowledge and managing improvement. This paper presents how Multi-agent system could be associated to CBR and Decomposition reasoning in order to be more efficient during the enterprise modelling.

A Multi-agent System for Selecting Portfolio of New Product Development Projects

This paper is concerned with designing a multi-agent approach for evaluating new products and selecting product portfolio. In today’s companies it is widespread to execute many new product projects simultaneously. As these projects require resources that are available in the limited quantities, there is the need to select the most promising set of new product for development. The evaluation of new product projects involves many agents that analyse the customer requirements and information acquired from an enterprise system, including the fields of sales and marketing, research and development, and production. The company’s resources, performance metrics, and the identified relationships are stored in knowledge base that is specified according to the framework of constraint satisfaction problem. The relationships are sought with the use of fuzzy neural system and described in the form of if-then rules.

Agent Based Approach for Modeling Disturbances in Supply Chain

The aim of the paper is to present the agent based approach for modeling disturbances in supply chain. An introduction to the issue of Agent-Based Modeling is provided. The paper describes in detail the modeled area of a supply chain, taking into account different modeling techniques. Disturbances (selected and highlighted by the authors) are identified and modeling methods are discussed. Two selected disturbances are modeled using of agent-based approach. The research highlights of the performed works are as follows: identifying disturbances in a supply chain, which can be modeled with use of the ABS approach and demonstrating how to model the chosen disturbances by using the above method of modeling.